Abstract
The paper discusses the application of hyper populated ant colonies to the well-known traveling salesman problem (TSP). The ant colony optimization (ACO) approach offers reasonably good quality solutions for the TSP, but it suffers from its inherent non-determinism and as a consequence the processing time is unpredictable. The paper tries to mitigate the problem by a substantial increase in the number of used ants. This approach is called ant hyper population and it could be obtained by increasing the number of ants in a single colony assigning more than one colony to solve the same task or both. In all cases the level of non-determinism decreases and thus the number iterations could be reduced. Parallel implementation of the ACO makes it possible to reduce drastically the processing time. The paper compares two ways of implementation of the parallelism using the sockets or the RMI--remote method invocation mechanisms. The paper concentrates on the classical static version of the TSP, but preliminary experiments indicate that such an approach could be even more useful for dynamic TPSs.
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